HarveyAI·Software Engineer·Onsite - Coding / Algorithms·Intermediate

Intermediate

May 2026

Summary

Coding round at HarveyAI for a software engineer role, one algorithmic problem centered on text highlighting with overlapping ranges. Pretty focused interview, no fluff.

Questions Asked (1)

Given a string and a list of highlight ranges that may overlap, produce the final highlighted output by merging overlapping ranges into contiguous spans. How would you approach this, and what's the time complexity?

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

The core idea is a sweep-line interval merge, sort the ranges and walk through them collapsing overlaps.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the problem: ranges are inclusive/exclusive, input format, and output format. Then propose sorting the ranges by start index and merging overlapping or adjacent intervals in a single pass, building the final highlighted string by inserting markers around merged spans. Analyze time complexity as O(n log n) due to sorting, with O(n) space for the output.

Pro tip: Mention edge cases like empty ranges, ranges covering the entire string, and adjacent ranges that should merge (e.g., [0,2] and [2,5] if inclusive). Also, discuss whether to modify the string in-place or build a new one, and consider Unicode or multi-byte characters if relevant.

1. Clarify requirements and edge cases

Ask about range inclusivity, input/output format, and how to handle empty ranges or ranges outside the string. Confirm whether adjacent ranges should merge.

2. Sort and merge intervals

Sort the ranges by start index. Iterate through them, merging overlapping or adjacent intervals into a list of non-overlapping spans.

3. Construct the highlighted output

Build the result string by iterating through the original string and inserting highlight markers at the start and end of each merged span.

4. Analyze time and space complexity

State that sorting takes O(n log n) time, merging takes O(n), and building the output takes O(m) where m is the string length. Overall O(n log n + m) time and O(n + m) space.

5. Discuss trade-offs and optimizations

Mention alternatives like using a difference array for O(n + m) time if ranges are bounded, or handling streaming input. Discuss whether to merge in-place or create a new string.

Key Points to Mention

Sorting ranges by start index is key to efficient merging.
Merge condition: next.start <= current.end (or < if exclusive) for overlap; also consider adjacency if inclusive.
Time complexity: O(n log n) for sorting, O(n) for merging, O(m) for output construction.
Space complexity: O(n) for merged intervals, O(m) for output string.
Edge cases: empty ranges, ranges covering entire string, adjacent ranges, invalid ranges.
Alternative approaches: difference array for O(n + m) if range bounds are small, or interval tree for dynamic queries.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.